---
title: Middle ML/MLOps Engineer at International project (Poland IT relocation group)
description: 🔥 **Hiring: Middle ML / MLOps Engineer**
---

# Middle ML/MLOps Engineer

**Company:** International project (Poland IT relocation group)  
**Location:** Remote (EU)  
**Posted:** 2026-09-23  
**Apply by:** 2026-11-07

**Tags:** python, backend, data

[Apply / View original posting](https://t.me/Pol_relocation/57342)

## Job description

🔥 **Hiring: Middle ML / MLOps Engineer**

We are looking for an experienced **Middle ML / MLOps Engineer (3+ years of experience)** to join an international project! In this role, you will design, build, and deploy production-scale machine learning and Generative AI / LLM-based applications in a cloud-native environment.

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📌 **Workload:** Full-time (100% Remote)

🗣 **Language:** English (Fluent — daily technical communication)

💻 **Tech Stack:** Python, AWS (SageMaker), Docker, Kubernetes, PySpark, FastAPI/Flask, MLOps (MLflow / Kubeflow), LLMs

🌍 **Location:** Remote within EU (**must hold EU Citizenship, PR, or a valid EU Work/Residence Permit**)

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🎯 **Key Responsibilities:**

* Design, develop, and deploy production-grade ML and LLM-based applications.
* Build and maintain robust MLOps platforms and CI/CD pipelines for machine learning workflows.
* Automate model training, evaluation, deployment, monitoring, and continuous improvement.
* Develop cloud-native ML infrastructure using AWS, SageMaker, Docker, and Kubernetes.
* Build reliable backend APIs and microservices using FastAPI or Flask.
* Collaborate closely with product, software engineering, and data teams.

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🛠 **Requirements:**

* **3+ years of commercial experience** as an ML Engineer, MLOps Engineer, or in a related field.
* Strong hands-on experience with **Python** and developing production-ready services with **FastAPI / Flask**.
* Proven experience with **AWS** (specifically **Amazon SageMaker**).
* Hands-on experience with **Docker** and **Kubernetes** for deployment and orchestration.
* Solid understanding of MLOps practices and ML lifecycle tools (**MLflow**, **Kubeflow**, or **SageMaker Pipelines**).
* Practical experience working with **LLMs / Generative AI** in production environments.
* Hands-on experience with **PySpark / Apache Spark**.
* **Fluent English** (B2+/C1) for effective collaboration with cross-functional teams.

⭐️ **Nice to Have:**

* Experience with recommendation systems, NLP, or forecasting use cases.
* Knowledge of model monitoring and observability tools.

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📩 **To Apply:**
Send your CV and expected hourly rate to @elizabeth_interexy

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